Salivary Cortisone to Estimate Cortisol Exposure and Sampling Frequency Required Based on Serum Cortisol Measurements

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Abstract

Context Population studies frequently measure cortisol as a marker of stress, and excess cortisol is associated with increased mortality. Cortisol has a circadian rhythm, and frequent blood sampling is impractical to assess cortisol exposure. We investigated measuring salivary cortisone and examined the sampling frequency required to determine cortisol exposure. Methods Serum and saliva with cortisol and cortisone were measured by liquid chromatography-Tandem mass spectrometry in independent cohorts. The relationship between serum cortisol and salivary cortisone was analyzed in cohort 1 using a linear mixed effects model. The resulting fixed effects component was applied to cohort 2. Saliva cannot easily be collected when a patient is sleeping, so we determined the minimum sampling required to estimate cortisol exposure [estimated area under the curve (eAUC)] using 24-hour cortisol profiles (AUC 24) and calculated the relative error (RE) for eAUC. Results More than 90% of variability in salivary cortisone could be accounted for by change in serum cortisol. A single serum cortisol measurement was a poor estimate of AUC 24, especially in the morning or last thing at night (RE >68%); however, three equally spaced samples gave a median RE of 0% (interquartile range,-15.6% to 15.1%). In patients with adrenal incidentalomas, eAUC based on three serum cortisol samples showed a difference between those with autonomous cortisol secretion and those without (P = 0.03). Interpretation Accepting that most people sleep 7 to 8 hours, â 1/48-hourly salivary cortisone measurements provide a noninvasive method of estimating 24-hour cortisol exposure for population studies.

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Harrison, R. F., Debono, M., Whitaker, M. J., Keevil, B. G., Newell-Price, J., & Ross, R. J. (2018). Salivary Cortisone to Estimate Cortisol Exposure and Sampling Frequency Required Based on Serum Cortisol Measurements. Journal of Clinical Endocrinology and Metabolism, 104(3), 765–772. https://doi.org/10.1210/jc.2018-01172

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